Engineering Management with a Focus on AI Integration
Birchwood Hotel & O.R. Tambo Conference Centre, Boksburg, Johannesburg
Accredited with ECSA — 3 CPD points.
About this programme
Technical excellence no longer guarantees engineering leadership. Managers are now expected to deliver projects, develop people and make sense of the analytics and automation tools arriving in their plants — often in the same week.
This three-day intensive gives engineering professionals both the management foundations and the AI-specific skills the role now demands. Day one covers engineering management fundamentals: project planning, leadership and lean management.
Day two moves into advanced skills — systems integration, quality management and financial control. Day three is dedicated entirely to AI in engineering: predictive analytics, risk assessment, automation tooling and the ethical considerations that accompany them.
Course content
The workshop programme, day by day.
Fundamentals of engineering management
- Introduction to engineering management: scope, roles and responsibilities
- Key management principles applied in engineering environments
- Project management basics: planning, scheduling, budgeting and risk management
- Leadership and team dynamics in engineering projects
- Lean management principles and application
- Communication and conflict resolution for engineering managers
- Case studies on successful engineering management practices
Advanced engineering management skills
- Systems engineering and integration management
- Quality management and continuous improvement (Lean, Six Sigma)
- Resource allocation, procurement and supply chain considerations
- Financial management and cost control in engineering projects
- Decision-making tools and techniques: analytical and quantitative methods
- Managing innovation and technology development within engineering teams
- Practical exercises: complex project scenarios and problem-solving
The role of artificial intelligence in engineering management
- Overview of artificial intelligence and its relevance to engineering management
- AI applications in project planning, predictive analytics and risk assessment
- Enhancing decision-making through AI-driven data analysis
- Automation and AI tools for improving productivity and efficiency
- Real-world examples: AI in engineering design, maintenance and operations
- Ethical considerations and challenges in adopting AI in engineering management
- Interactive session: exploring AI technologies and their potential impact on future engineering management
Who should attend
- Engineering Managers & Project Managers
- Team Leaders & Department Heads
- Systems Engineers & Integration Specialists
- Quality & Continuous Improvement Professionals
- Technical Directors & Heads of Engineering
- R&D Managers & Innovation Leaders
- Any engineer seeking to leverage AI tools in their discipline
Ready to elevate your team's capability?
Request a proposal, book a facilitator, or schedule a discovery call. Our advisors respond within one business day.